NetworkGym Client

📋 NetworkGym Docs Website

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The NetworkGym Client stands as a Python-centric client library created for NetworkGym, an innovative Simulation-as-a-Service framework crafted to democratize network AI research and development. This Client establishes a remote connection to the NetworkGym Server/Environment hosted on the cloud, facilitating agent training. At present, NetworkGym Client supports four environments: nqos_split, qos_steer, network_slicing and rmcat.

💡 Overview

This repository includes the network_gym_client components. The network_gym_server and network_gym_env components are hosted in the cloud. After cloning this repository, users can launch the network_gym_client to remotely connects to the newtork_gym_server and newtork_gym_env via the northbound interface.

• network_gym_client
  • gymnasium.env: a customized gymnasium environment that communicates with the agent.
  • adapter: transform the network stats measurements to obs and reward; translate action to policy that can be applied to the network.
  • northbound_interface: communicates network confiugration, network stats and policy between client and network_gym server/environment.

⌛ Installation

1. clone this repository

git clone https://github.com/netsim-llc/networkgym.git

3. install Python 3.11 on Ubuntu 24.04

    sudo add-apt-repository ppa:deadsnakes/ppa
    sudo apt update
    sudo apt install python3.11
    sudo apt install python3.11-venv

2. create venv and install requirements.txt

    python3.11 -m venv myenv
    source myenv/bin/activate
    cd ./networkgym
    pip3 install -r requirements.txt

3. create common_config_local.json

   cd ./network_gym_client
   cp ./common_config.json ./common_config_local.json

4. obtain your username and PAT (personal access token)

    - Go to ns3.netsimsolutions.com and create an account if you don't have one.
    - Go to subscription and upgrade to "Pro". 
    - Click on Account Manager (top-right corner).
    - Select Personal Access Token (available for "Pro" users only).
    - Optionally, generate a new token by clicking Refresh—note that the new token will become active after 2 hours.

5. update common_config_local.json

  "server_ip": "51.81.221.50",
  "server_port": 8088,
     ...
  "session_name": [username],
  "session_key": [PAT]

🚀 Start NetworkGym Client

• Start the demo client using the following command:

python3 start_client.py

• If "enable_terminal_redering" equals true, the network stats will be rendered in the terminal
• If "enable_wandb" equals true, you can visualize the output using the WanDB website.
• run the example python3 script for celllular RAN slicing (https://netsim-llc.github.io/networkgym/environments/mx_network_slicing/cellular_network_slicing.html#cards-mx-cellular-slicing)

    python3 start_client_network_slicing.py 

📁 File Structure

📦 networkgym
┣ 📜 start_client.py
┗ 📂 network_gym_client
  ┣ 📜 adapter.py (➡️ WanDB)
  ┣ 📜 common_config.json
  ┣ 📜 env.py
  ┣ 📜 northbound_interface.py (➡️ network_gym_server and network_gym_env)
  ┗ 📂 envs
    ┗ 📂 [ENV_NAME]
      ┣ 📜 adapter.py
      ┗ 📜 config.json

• Excuting the 📜 start_client.py file will start a new simulation. To change the environment, modify the env_name parameter. The 📜 common_config.json is used in all environments. Depends on the selected environments, the 📜 config.json and 📜 adapter.py in the [ENV_NAME] folder will be loaded. The 📜 adapter.py helps preparing observations, rewards and actions for the selected environment.

• The 📜 start_client.py create a NetworkGym environment, which remotely connects to the ns-3 based NetworkGym Simualtor using the 📜 northbound_interface. 📜 start_client.py also uses random samples from the action space to interact with the NetworkGym environment. The results are synced to ➡️ WanDB database.

  📚 How to reference "NetworkGym"?

Please use the following to reference "NetworkGym" in your paper if it is used to generate data for the paper:

Menglei Zhang and Jing Zhu, "NetworkGym: Democratizing Network AI via Simulation-as-a-Service", https://github.com/netsim-llc/networkgym